开源工具用于实时和自动分析基于滴滴的微流体
Joana P Neto1, Ana Mota1, Gonçalo Lopes2
1CENIMAT|i3N, Department of Materials Science, NOVA School of Science and Technology, NOVA University of Lisbon and CEMOP/UNINOVA, Campus de Caparica, Caparica, Portugal. joana.neto@campus.fct.unl.pt.
Lab on a chip
|June 21, 2023
概括
研究人员现在可以很容易地使用开源的邦赛视觉编程语言实时监测微流体滴. 这种具有成本效益和用户友好的工具可以实现精确的滴滴分析,以提高实验的可扩展性和自动化.
科学领域:
- 微流体学 微流体学
- 生物技术是生物技术.
- 图像分析 图像分析
背景情况:
- 基于滴滴的微流体可实现高通量选,但需要先进的实时监控.
- 目前的监测方法复杂,昂贵,并非所有研究人员都能轻松获得.
- 微流体系统的可扩展性和自动化受到滴滴检测技术的局限性阻碍.
研究的目的:
- 验证可访问的,开源的视觉编程语言,用于实时微流体滴滴测量.
- 开发一个具有成本效益,无标签的监控系统,使用现成的组件.
- 为具有不同专业水平的研究人员提供一个用户友好的工具.
主要方法:
- 利用邦赛视觉编程语言处理明亮场显微镜图像的图像.
- 开发了一个低成本的光学系统,随时可用的硬件组件.
- 特性滴滴参数包括半径,循环速度和生产频率.
主要成果:
- 证明了使用邦赛的微流体液滴的准确实时测量.
- 实现了用于滴滴检测和表征的高处理速度.
- 通过不同用户专业知识水平,验证了与已建立的软件 (ImageJ) 进行比较的结果.
结论:
- 基于邦赛的系统为实时滴滴监控提供了强大,简单和经济有效的解决方案.
- 这种方法降低了先进的微流体实验的进入壁垒.
- 可立即集成到实验室工作流程中进行实时数据分析和闭环控制.
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